[
https://issues.apache.org/jira/browse/SPARK-3098?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Guoqiang Li updated SPARK-3098:
-------------------------------
Description:
{code}
val c = sc.parallelize(1 to 7899).flatMap { i =>
(1 to 10000).toSeq.map(p => i * 6000 + p)
}.distinct().zipWithIndex()
c.join(c).filter(t => t._2._1 != t._2._2).take(3)
{code}
=>
{code}
Array[(Int, (Long, Long))] = Array((1732608,(11,12)), (45515264,(12,13)),
(36579712,(13,14)))
{code}
was:
I do not know how to reproduce the bug.
This is the case. When I was in operating 10 billion data by groupByKey. the
results error:
{noformat}
(4696501, 370568)
(4696501, 376672)
(4696501, 374880)
.....
(4696502, 350264)
(4696502, 358458)
(4696502, 398502)
......
{noformat}
=>
{noformat}
(4696501,ArrayBuffer(350264, 358458, 398502 ........)),
(4696502,ArrayBuffer(376621, ......))
{noformat}
code :
{code}
val dealOuts = clickPreferences(sc, dealOutPath, periodTime)
val dealOrders = orderPreferences(sc, dealOrderPath, periodTime)
val favorites = favoritePreferences(sc, favoritePath, periodTime)
val allBehaviors = (dealOrders ++ favorites ++ dealOuts)
val peferences= allBehaviors.groupByKey().map { ... }
{code}
spark-defaults.conf:
{code}
spark.default.parallelism 280
{code}
> In some cases, operation zipWithIndex get a wrong results
> ----------------------------------------------------------
>
> Key: SPARK-3098
> URL: https://issues.apache.org/jira/browse/SPARK-3098
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.0.1
> Reporter: Guoqiang Li
> Priority: Critical
>
> {code}
> val c = sc.parallelize(1 to 7899).flatMap { i =>
> (1 to 10000).toSeq.map(p => i * 6000 + p)
> }.distinct().zipWithIndex()
> c.join(c).filter(t => t._2._1 != t._2._2).take(3)
> {code}
> =>
> {code}
> Array[(Int, (Long, Long))] = Array((1732608,(11,12)), (45515264,(12,13)),
> (36579712,(13,14)))
> {code}
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